CS461 OSU Capstone Tree Segmentation from Aerial Point Clouds
GitHub repo: https://github.com/gallegon/Capstone-TSFAPC
Created by Mark G, Nicholai G, and Samuel F.
Basic requirements: Python, numpy, scipy, gdal, pdal.
To see full documentation of installation and usage please visit our GitHub pages site at: https://gallegon.github.io/Capstone-TSFAPC/
To run the algorithm use the provided ts_cli.py
script:
python ts_cli.py context_file
Where context_file
is the path to the input context JSON file.
There are example JSON config files in the tests/ directory.
These files allow the user to specify parameters for the tree
segmentation algorithm.
Alternatively, the treesegmentation.treeseg_lib
module can be imported and used in a custom Python script.
There are several features that we were unable to achieve during in our Capstone timeline:
- Integrating statistics processing into our script.
- Full integration with PDAL pipeline.
- Full integration as a QGIS plugin.
- Optimizations for hierarchy building, weighted graph, and partitioning steps.
A main goal of this project was to provide an extensible base for this tree segmentation algorithm.
- Further optimization of the hierachy building, weighted graph, and partitioning steps.
- Further extending the QGIS integration.
- Building the algorithm as a filter and/or writer for PDAL (in C++), reducing the need for Python to be used for processing. Using python as a front end to an interface (command line or GUI in QGIS) and leaving the heavy lifting of the algorithm to compiled code.
- More packaging for different platforms (Mac/Linux).